1 Monday 24

Processing and analysis of microscopic images in biomedicine, 24th-28th April 2017

24th April – Monday

9.00-9.45 Digital image formation, Michaela Efenberková, theoretical lecture

Lecture introduces you into formation of digital images, basic principles of cameras, image

discretization. It will tell you what pixels, pixel size, bit depth, magnification and field of

vision are. Luminescence, intensity and color will be described as well.

Keywords: image formation, pixel, intensity.

9.50-10.35 Digital image terminology, Ivan Novotný, theoretical lecture

The lecture will explain basic terms in the field of digital image processing, e.g., resolution

and sampling using explanation of Nyquist theorem, histogram and its reading, image depth

(8/16/24/32 bit), noise, LUT.

Keywords: resolution, sampling, histogram.

10.55-11.40 Introduction into Fiji - Part1, Ivan Novotný, practical in one group

What is Fiji useful for? What is a multipage image? Where do we have colors coded? Grayscale vs. RGB; channels vs. stacks, hyperstacks. Aims: We will do Fiji installation and solve update issues, demonstrate file opening/file type setting/bit depth setting/file saving, contrast/brightness adjusting/image resizing. Then we will work with channels, will split and merge images, define channel color, learn image stacks/hyperstacks, something about image dimensionality and setting image properties.

Requirements: laptop with Fiji, Java up to date Keywords: file type, image adjustment, stack, hyperstack, multipage image, LUT.

11.45-12.30 Introduction into Fiji - Part2, Anna Malinová, practical in one group

Aim: In this practical we will continue with our work in Fiji and will learn basics of image manipulation. 13.30-14.15 Introduction into Fiji – Part3, Anna Malinová, practical in one group

Aims: We will pay attention to thresholding, image filtering and enhancement and denoising. We will create animations, demonstrate orthogonal views, montages, RGB image manipulation, MIP, Z-Project.

Requirements: laptop with Fiji, Java up to date Keywords: thresholding, image filtering, denoising, orthogonal views.

2 Monday 24

14.20-15.05 Image analysis in Fiji, Michaela Efenberková, practical in one group

Aims: We will examine several simple image analysis tools available in Fiji. Using examples, we will learn how to work with ROI manager, how to use profile plots. We will use thresholding to measure characteristics of objects in the image, find edges and maxima in the image. We will count particles in 2D and 3D, perform 2D image registration, create a kymograph and learn how to use plugins. Requirements:

laptop with Fiji

image data

plugin 3D ImageJ Suite

both images and the plugin can be downloaded from the course webpage

Keywords: ROI, thresholding, image registration. 15.10-15.55 Fiji: Macros - Introduction into IJM language, Martin Čapek, theoretical lecture

The lecture will give you basics of ImageJ Macro (IJM) language. This includes knowledge of variables, operators, conditional and looping statements, strings, debugging macros, built-in macro functions, which is necessary for creating your own macros. Keywords: IJM – ImageJ Macro language, macro functions.

3 Tuesday 25

25th April - Tuesday 9.00-9.45 Fiji: Using macros for data processing and analysis, Martin Čapek, practical in one group

Aims: Introduction into macro recorder and macro editor. Creating macros for segmentation and counting nuclei in multiple images by using macros; the automatic processing of open images. Requirements:

laptop with Fiji

image data can be downloaded from the course webpage Keywords: macro recorder, macro editor, generic macros.

9.50-10.35 Image acquisition conditions for proper deconvolution, Ivan Novotný, theoretical lecture

The image acquisition and requirements for successful deconvolution will be described

together with description of various microscope types and their specificity. Quality of

images regarding deconvolution results will be discussed as well.

Keywords: widefield fluorescent microscope, confocal microscope, STED, point spread

function (PSF), z-stack, SNR.

10.55-11.40 Huygens: Image deconvolution I, Ivan Novotný, practical in one group

11.45-12.30 Huygens: Image deconvolution II, Ivan Novotný, practical in one group

Aims: Practical deconvolution of various microscopic data. Image metadata and image parameters for the deconvolution. Parameters of the deconvolution – SNR, iterations, quality threshold.

Requirements: Huygens Professional Trial Keywords: Image metadata, image parameters, deconvolution, Huygens, SNR.

13.30-14.15 Segmentation methods, Martin Čapek, theoretical lecture

We will define what segmentation is, will classify segmentation methods and will describe

individual basic approaches, like region growing and splitting, Watershed transform,

thresholding, Hough transform, model-based comparisons, border areas, active contours,

and others. We will show how to use Fiji for solution of segmentation tasks. Practical

examples from biomedical practice – using region growing for fusion of CT and MRI data

sets, line segmentation for stitching medical images will be exemplified a well.

Keywords: segmentation, object finding, thresholding.

14.20-15.05 Fiji: Using segmentation for detection of structures in various microscopic images I,

Martin Čapek, practical in one group

15.10-15.55 Fiji: Using segmentation for detection of structures in various microscopic images II,

Martin Čapek, practical in one group

Aims: 1. To do simple segmentation tasks using a micro CT image of a tooth; 2. To detect

circular objects – sections through an embryonic mouse intestine – in a confocal image

using the Hough transform; 3. To automatically count number of red blood cells in a phase-

contrast image by the Watershed transform; 4. To detect erythrocytes in a DIC (differential

4 Tuesday 25

interference contrast) image using template matching; 5. To detect various biological

objects with different quality of their borders in an image using level sets.

Requirements:

laptop with Fiji

image data

installed plugins - Hough_Circles.class, ij-plugins_toolkit.jar, KHKs_StackSRG.jar, Create_Template.jar

both images and plugins can be downloaded from the course web page Keywords: Hough transform, region growing, Watershed transform, level sets.

5 Wednesday 26

26th April - Wednesday

9.00-9.45 I am watching you or what it means „tracking“, Michaela Efenberková, theoretical lecture

Very fast development of light microscopy methods allows us to collect large amount of

dynamic data. We are not only able to localize organelles or protein complexes but also

individual molecules in time. In this lecture we will focus on methods used to determine the

parameters of the movement of intracellular organelles and protein complexes, specifically

their velocity and trajectory. Together with changes in organelle sizes and changes in

fluorescence, the resulting information represents an output that uniquely characterizes

the specific process. Examples from projects that enabled us to clarify character of

movement and interactions of intra-nuclear proteins, localization of proteins into cell

membranes and dynamics of endoplasmic reticulum will be presented.

Keywords: tracking, trajectory, localization.

9.50-10.35 Fiji: Tracking – practicals, Michaela Efenberková, practical in one group

Aims: To track objects in the image during the time lapse experiment using several Fiji plugins. The participants will obtain several time series with moving objects and areas. Using Fiji plugins we will track the objects in time, characterize their movement using velocity and trajectory, and compare the results. Requirements:

laptop with Fiji

image data

plugins ParticleTracker, TrackMate

both images and plugins can be downloaded from the course webpage

Keywords: tracking, movement characterization, localization.

10.55 - 11.40 Evaluation of colocalization in microscopic images, Martin Čapek, theoretical lecture

This lecture explains you conditions for getting images suitable for colocalization, with

image pre-processing, and describes basic colocalization approaches, like Pearson’s

correlation coefficient, Manders’ coefficients, Costes’ methods, Van Steensel’ approach.

Object based colocalization, free programs and Fiji plugins available for image colocalization

will be discussed as well.

Keywords: colocalization, image similarity, Pearson’s correlation coefficient.

11.45-12.30 Fiji: Evaluation of colocalization in various

microscopic images, Martin Čapek, practical

in one group

The goal of this exercise is to evaluate the colocalization in high quality image data using JACoP plugin (Just Another Colocalization Plugin) and to analyze low quality noise images and data with bleed through using Coloc 2 plugin. Images of a dimeric protein stained with greed and red dyes, respectively, and images of cells stained by GFP and DAPI will be used as examples.

6 Wednesday 26

Requirements:

laptop with Fiji

image data

installed plugin - jacop_.jar

both images and the plugin can be downloaded from the course web page

Keywords: low quality microscopic data, colocalization, JACoP, Coloc 2.

13.30-14.15 3D and 4D image visualization and analysis in Imaris, Matthias Ascherl,

BITPLANE, www.bitplane.com, theoretical lecture

Imaris includes a set of key tools, which cater for the needs of researchers in live cell imaging and, in particular, developmental biology, but also in Neurobiology. Furthermore, it addresses the ability to work on large datasets. The available tools include:

Visualization of terabyte multidimensional data sets

Detection, tracking and analysis of cells and organelles

Tracking of cell division, lineage analysis

Rotational and translational drift correction

Angle measurements

Neuron and spine analysis

Colocalization studies

A wide range of plugins (XTensions) and advanced interactive plotting for results exploration and comparison between samples

14.20-15.05 Imaris: Examples of interactive image analysis and visualization, Matthias Ascherl,

BITPLANE, www.bitplane.com, practicals in two separated groups

Aims: Introduction into the basic functionalities for experiment data management, visualization and segmentation of the 3D and 4D microscopy datasets. Multiple volume rendering and modes, clipping planes, cross-section slices, animations and snapshots will be demonstrated:

User interface - Arena/Surpass/Vantage

Surface detection and extraction of statistical data

Spots detection and extraction of statistical data

Tracking examples

Colocalization

7 Wednesday 26

15.10-15.55 Ellipse: Evaluation of clustering and colocalization in electron microscopy, Vlada

Philimonenko, practicals in two separated groups

Aims: The course includes the introduction into the topic of the quantitative evaluation of the spatial dependencies and associations in immunolabeling in transmission electron microscopy (TEM) images. Immunolabeling of the tissues or cells in TEM is the alternative approach to immunostaining in the images acquired using fluorescent microscopy (FM). TEM labelling shares the molecular mechanisms with the immunolabeling technique in FM. Nevertheless, the method of detection is different. TEM visualization technique requires the presence of the metal nanoparticles, which are conjugated with the antibodies and substitute the different fluorescent chemical compounds in FM. As visualization method is different, another set of evaluation techniques is applied. Requirements:

laptop with Ellipse software package

plugins and image data can be downloaded from the course webpage Keywords: electron microscopy, immunolabeling, nanoparticles, spatial statistics.

8 Thursday 27

27th April - Thursday

9.00-9.45 Electron microscopy tomography, Jindřiška Fišerová, theoretical lecture

During this lecture you will learn what tomography is including various types of tomography

systems – X-ray, CT, MRI, 3D TEM, with explanation of tomograms. 3D electron tomography

(3D TEM) – from experimental design to tomogram, advantages and disadvantages, how

and when to apply tomography, practical examples.

Keywords: tomography, electron microscopy, tomogram.

9.50-10.35 Single particle analysis, Lukáš Maršálek, Eyen SE, www.eyen.se, theoretical lecture

Single Particle Analysis (SPA) is currently the

most popular 3D cryo-electron microscopy

method for determining high-resolution

structures of macromolecular complexes.

Advancements in both hardware and

software allow it nowadays to reach a quasi-

atomic resolution of around 3A even on

asymmetric particles, rivaling for the first

time in history the resolution of X-ray

crystallography. What was once an exotic

method is now a vital tool for modern

structural biology research. In this talk I will

persuade you that SPA is more than a set of

boring gray images you associate electron microscopy with, explaining along the way the

method’s core principles, utility in structural biology research and most prominent results

to date. Finally, I will also touch topics important for X-ray crystallography practitioners

such as resolution definition and estimation and validation of the reconstructed structures.

Keywords: cryo-electron microscopy, immunolabeling, nanoparticles, spatial statistics.

10.55-11.40 Stereological methods and measurement of 3D data, Lucie Kubínová, theoretical lecture

We will introduce you into stereology and into

sampling in stereology and will describe

various stereological methods, like Cavalieri's

principle for measuring volume, point-

counting method, methods for measuring

length and surface area from thin sections,

methods based on focusing through thick

sections: disector principle for counting three-

dimensional particles (e.g., cells), methods for

length measurement of spatial curves (e.g., capillaries) and surface area.

Keywords: stereology, volume, surface area, length, number.

9 Thursday 27

11.45-12.30 3D image processing and geometrical modelling, Jiří Janáček, theoretical lecture

Main topics of the talk are the processing of 3D biomedical images and visualization of the spatial data. Detection of capillaries in confocal images and construction of 3D models from tomographic data or physical sections will be presented.

Data sources: CLSM, MRI, tomography, registration of physical slices.

Voxel size determination, correction of sample shrinkage.

Filtration, segmentation and isosurface detection.

3D visualization: volume and surface rendering; visual cues: stereoscopy, motion, shading and texture.

Keywords: 3D reconstruction, triangulated isosurface.

13.30-14.15 Fiji: Image filtration / Morphological image processing and analysis, Jiří Janáček, practical

in one group

Aims: Basic microscopy image processing and segmentation with Fiji using linear filtration and mathematical morphology filters. Important features on 2D images (thick objects, fibers, dots) and on 3D images (thick objects, surfaces, fibers, dots). Properties of image noise.

Gaussian filter and its action on noisy image features.

Morphological operations (erosion, dilation, opening, closing, volume opening) for artefacts removal.

Rolling ball and Lipschitz filter for background removal.

Watershed operation for separation of objects.

Requirements:

laptop with Fiji

both images and the plugin can be downloaded from the course webpage

Keywords: mathematical morphology, image noise, image filtration, Gaussian filter. 14.20-15.05 FRAP data analysis, Michaela Efenberková, theoretical lecture

One of the very important and also very fast microscopic methods for analysis of protein dynamics in a specific cell region is FRAP (fluorescence recovery after photobleaching). It is based on the principle that we are able to bleach the fluorescence of selected fluorescence proteins by their targeted high intensity illumination. In the illuminated region no recovery of the fluorescence is assumed, therefore, the fluorescence that starts to appear in the photobleached region results from proteins that come from unbleached areas. According to properties of the curves describing the fluorescence recovery we are able to deduce the amount of mobility of the specific protein. In this lecture the FRAP method and its

10 Thursday 27

modifications will be presented and especially possibilities of its evaluation will be discussed. Keywords: photobleaching, FRAP, FRAP parameters, mobility.

15.10-15.55 Fiji: FRAP data analysis, Michaela Efenberková, practical in one group

Aims: To determine the mobility of small nuclear ribonucleoprotein particles (snRNP) that move around and interact inside the cell nucleus using FRAP (fluorescence recovery after photobleaching). The participants will obtain time series of fluorescence images with snRNP-GFP. A complete FRAP experiment, i.e. the situation before photobleaching, closely after photobleaching and in a few time points during the recovery will be provided. The aim of this task is to evaluate the presence of the signal in both bleached and reference areas and to determine the representation of mobile and immobile protein fraction. We will also examine several ways how to determine other FRAP curve parameters. At the end we will compare the results. Requirements:

laptop with Fiji

image data

script http://fiji.sc/Analyze_FRAP_movies_with_a_Jython_script

both images and the script can be downloaded from the course webpage

Keywords: FRAP, curve fitting, curve parameters, mobility.

18.00-21.00 Informal party with refreshments – PIZZA NUOVA, Revoluční 1, Prague

Connection: metro Náměstí Republiky

We invite you all to this restaurant to enjoy Degustacione Campania:

„All You Can Eat” – antipasti buffet, pizza Napoletana and house-made pasta

http://pizzanuova.ambi.cz/en/menu?id=17286

11 Friday 28

28th April - Friday 9.00-9.45 2D stereology - Cavalieri's principle and point counting method, Barbora Radochová,

practicals in two separated groups

Aims: To estimate volume of a rat's brain and a carrot using Cavalieri's principle and point counting method. The participants will learn about principle of systematic uniform random sampling. For the rat's brain volume estimation, we will use acquired image data and FIJI plugin Lin Sys Cycloides. For the carrot volume estimation we will work with real carrots and worksheets. Requirements:

laptop with Fiji

Internet (web page: www.random.org – True Random Number Generator)

Installed plugin Lin Sys Cycloides (can be downloaded from the course web page)

rat's brain image data (can be downloaded from the course webpage)

carrot, graduated cylinder, razor blade, worksheets, point counting grid (all will be distributed)

Keywords: 2D stereology, point counting method, Cavalieri's principle.

9.00-10.35 3D stereology - Fakir method and Disector, Barbora Radochová, practicals in two

separated groups

Aims: We will try two different 3D methods: 1) Fakir method for estimation of volume and surface of a human Langerhans islet and 2) Disector method for estimation of the density of particles. The participants will learn about the principle of the Fakir method; the principles of particle counting in 2D (Gundersen) and 3D (Disector) will be explained. We will use Fakir software and plugin Disector in FIJI. Requirements:

laptop with FIJI (Windows 7 or newer)

installed Fakir sw (can be downloaded from the course web page)

plugin Disector

image data (can be downloaded from the course web page)

Keywords: 3D stereology, fakir method, disector method, Langerhans islet volume and surface, particle counting.

10.55-11.40 Scale setting, 3D image filtration and measurement in Fiji, Jiří Janáček, practicals in two

separated groups

Aims: To learn basic skills in 3D image processing. Counting of cell nuclei in brain sample, measurement of tobacco cell volume and measurement of length of capillary system in skeletal muscle.

1. Voxel size determination, correction of sample shrinkage.

2. Filtering out the noise by Gaussian, removal of nonspecific staining by Rolling ball, image thresholding.

3. Objects counting, area and length measurement in 2D image, volume, surface area and length measurement in 3D image.

12 Friday 28

Requirements:

laptop with Fiji

image data (can be downloaded from the course web page)

Keywords: specimen shrinkage, Gaussian filtering, rolling ball. 11.45-12.30 Triangulated surfaces reconstruction, Jiří Janáček, practicals in two separated groups

Aims: To reconstruct placenta villus and tobacco cell from CLSM images and eukaryotic cell from EM images of physical slices.

1. Contours drawing, registration of physical slices. 2. Isosurface detection 3. Animation of 3D models.

Requirements:

laptop with Fiji

image data (can be downloaded from the course web page) Keywords: contour drawing, isosurface detection.

12.30-13.00 Final participant test

14.00-14.30 Final course evaluation (Pavel Hozák)